An investigation into the uncertainty revision process of professional forecasters

Clements, M. P. ORCID: https://orcid.org/0000-0001-6329-1341, Rich, R. and Tracy, J. (2025) An investigation into the uncertainty revision process of professional forecasters. Journal of Economic Dynamics and Control, 173. 105060. ISSN 1879-1743 doi: 10.1016/j.jedc.2025.105060

Abstract/Summary

Following Manzan (2021), this paper examines how professional forecasters revise their fixed-event uncertainty (variance) forecasts and tests the Bayesian learning prediction that variance forecasts should decrease as the horizon shortens. We show that Manzan’s (2021) use of first moment “efficiency” tests are not applicable to studying revisions of variance forecasts. Instead, we employ monotonicity tests developed by Patton and Timmermann (2012) in our first known application of these tests to second moments of survey expectations. We find strong evidence that the variance forecasts are consistent with the Bayesian learning prediction of declining monotonicity.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/120586
Identification Number/DOI	10.1016/j.jedc.2025.105060
Refereed	Yes
Divisions	Henley Business School > Finance and Accounting
Publisher	Elsevier
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